OCR Text |
Show ing the signals upstream and downstream, the signals attenuate as they pass through the ceramic burner. From the measured concentration fluctuations, the probability density distributions were calculated. Figure 7 shows the probability density distribution of the air ratio on the downstream side and the Gaussian distribution for a standard deviation of 0.08. The distribution varies from 1.2 to 1 .55 and shows a similar distribution to the Gaussian, indicating that the concentration fluctuations can be approximated by a Gaussian distribution. From the probability density distributions for each mixing condition, the standard deviations were calculated. Figure 8 shows the variation of the standard deviations with the air ratio. It is clear that the standard deviations decrease after the mixture passes the burner. In the perfect mixing case, the standard deviations are small. As described above, these can be attributed to noise in the light sensor. Figure 9 shows the measured temperature fluctuations for a flame of air ratio of 1.4. The temperatures were 6 7~--------------------~ 6 £5 en c (J) 4 o :=>3 :.0 ~ ..0 2 o ~ a... Downstream Gaussian distribution measured I 0=0.08 O~----~ ____ ~ __ -W~~-W 1.0 1 .1 12 1 .3 1.4 1.5 1.6 1.7 Air ratio Rg.7 Probability density distribution compared with Gaussian distribution. 0.2 ~----------------------- ~ Downstream (Perfect mixing) -.-Downstream (Partial mixing) ~ Upstream (Perfect mixing) § 0.15 - Upstream (Partial mixing) :.t:= .m:; Q) -0 0.1 -0 ~ m -0 c: ~ 0.05 en Fig.8 Variation of standard deviation with air ratio calculated from air ratio fluctuations. measured 100 mm downstream from the center of the bumer. The effect of the radiation loss on the measured temperatures was not corrected. Similar to the fuel concentration fluctuations, temperatu re fluctuations are clearly present in the flame for the partial mixing case; this is in contrast to the small fluctuations in the perfectly premixed flame. |